atomicarchitects/equiformer_v2
[ICLR 2024] EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
This project offers a sophisticated AI model for materials scientists and computational chemists. It takes 3D atomic structures as input and accurately predicts their energy and forces, which are crucial for understanding material behavior and chemical reactions. This tool is designed for researchers and engineers working on novel materials discovery and optimization.
328 stars. No commits in the last 6 months.
Use this if you need highly accurate predictions of atomic forces and energies for 3D molecular or material structures, particularly for catalyst design and simulations.
Not ideal if you are a Python developer seeking a general-purpose library for building arbitrary equivariant models, or if you don't work with atomistic systems.
Stars
328
Forks
45
Language
Python
License
MIT
Category
Last pushed
Feb 11, 2025
Commits (30d)
0
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